{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,23]],"date-time":"2026-05-23T22:06:51Z","timestamp":1779574011092,"version":"3.53.1"},"reference-count":56,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neural Networks"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.neunet.2026.109081","type":"journal-article","created":{"date-parts":[[2026,5,10]],"date-time":"2026-05-10T14:26:35Z","timestamp":1778423195000},"page":"109081","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["KAB: A knowledge-aligned benchmark for reproducible evaluation of distantly supervised relation extraction"],"prefix":"10.1016","volume":"203","author":[{"given":"Bowen","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junhang","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9039-0318","authenticated-orcid":false,"given":"Yucong","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8940-1559","authenticated-orcid":false,"given":"Yaqing","family":"Nie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongmin","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4897-845X","authenticated-orcid":false,"given":"Zichao","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2124-3605","authenticated-orcid":false,"given":"Jingtao","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5550-8416","authenticated-orcid":false,"given":"Xutao","family":"Weng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaoli","family":"Su","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinfu","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.neunet.2026.109081_bib0001","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.109494","article-title":"Entity alignment based on relational semantics augmentation for multilingual knowledge graphs","volume":"252","author":"Akhtar","year":"2022","journal-title":"Knowledge-Based Systems"},{"issue":"2","key":"10.1016\/j.neunet.2026.109081_bib0002","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2022.103221","article-title":"NRAND: An efficient and robust dismantling approach for infectious disease network","volume":"60","author":"Akhtar","year":"2023","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.neunet.2026.109081_bib0003","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.109660","article-title":"Multilingual entity alignment by abductive knowledge reasoning on multiple knowledge graphs","volume":"139","author":"Akhtar","year":"2025","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"10.1016\/j.neunet.2026.109081_bib0004","series-title":"Proceedings of the 58th annual meeting of the association for computational linguistics","article-title":"TACRED revisited: A thorough evaluation of the TACRED relation extraction task","author":"Alt","year":"2020"},{"key":"10.1016\/j.neunet.2026.109081_bib0005","series-title":"Proceedings of the web conference","article-title":"RECON: Relation extraction using knowledge graph context in a graph neural network","author":"Bastos","year":"2021"},{"key":"10.1016\/j.neunet.2026.109081_bib0006","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2023.101900","article-title":"Reinforcement learning-based distant supervision relation extraction for fault diagnosis knowledge graph construction under industry 4.0","volume":"55","author":"Chen","year":"2023","journal-title":"Advanced Engineering Informatics"},{"key":"10.1016\/j.neunet.2026.109081_bib0007","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2024.128864","article-title":"Distantly supervised relation extraction with a meta-relation enhanced contrastive learning framework","volume":"617","author":"Chen","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neunet.2026.109081_bib0008","series-title":"Proceedings of the ACM web conference","article-title":"Knowprompt: Knowledge-aware prompt-tuning with synergistic optimization for relation extraction","author":"Chen","year":"2022"},{"key":"10.1016\/j.neunet.2026.109081_bib0009","series-title":"Proceedings of the conference of the North American chapter of the association for computational linguistics: Human language technologies","article-title":"Distantly supervised relation extraction with sentence reconstruction and knowledge base priors","author":"Christopoulou","year":"2021"},{"issue":"1","key":"10.1016\/j.neunet.2026.109081_bib0010","doi-asserted-by":"crossref","first-page":"1418","DOI":"10.1038\/s41467-024-45563-x","article-title":"Structured information extraction from scientific text with large language models","volume":"15","author":"Dagdelen","year":"2024","journal-title":"Nature Communications"},{"key":"10.1016\/j.neunet.2026.109081_bib0011","doi-asserted-by":"crossref","DOI":"10.1016\/j.iswa.2023.200244","article-title":"A survey on relation extraction","volume":"19","author":"Detroja","year":"2023","journal-title":"Intelligent Systems with Applications"},{"key":"10.1016\/j.neunet.2026.109081_bib0012","series-title":"Proceedings of the international conference on image processing, computer vision and machine learning (ICICML)","article-title":"Graph neural network-based entity extraction and relationship reasoning in complex knowledge graphs","author":"Du","year":"2024"},{"key":"10.1016\/j.neunet.2026.109081_bib0013","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.110195","article-title":"Exploiting global context and external knowledge for distantly supervised relation extraction","volume":"261","author":"Gao","year":"2023","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.neunet.2026.109081_bib0014","series-title":"Proceedings of the conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (EMNLP-IJCNLP)","article-title":"FewRel 2.0: Towards more challenging few-shot relation classification","author":"Gao","year":"2019"},{"key":"10.1016\/j.neunet.2026.109081_bib0015","series-title":"Findings of the association for computational linguistics: ACL-IJCNLP","article-title":"Manual evaluation matters: Reviewing test protocols of distantly supervised relation extraction","author":"Gao","year":"2021"},{"key":"10.1016\/j.neunet.2026.109081_bib0016","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.129858","article-title":"Distantly supervised relation extraction with multi-level contextual information integration","volume":"634","author":"Han","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neunet.2026.109081_bib0017","doi-asserted-by":"crossref","first-page":"2029","DOI":"10.1109\/TKDE.2025.3530467","article-title":"Mitigating the tail effect in fraud detection by community enhanced multi-relation graph neural networks","volume":"37","author":"Han","year":"2025","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.neunet.2026.109081_bib0018","doi-asserted-by":"crossref","first-page":"96912","DOI":"10.1109\/ACCESS.2020.2996642","article-title":"A novel document-level relation extraction method based on BERT and entity information","volume":"8","author":"Han","year":"2020","journal-title":"IEEE Access: Practical Innovations, Open Solutions"},{"key":"10.1016\/j.neunet.2026.109081_bib0019","series-title":"Proceedings of the joint international conference on computational linguistics, language resources and evaluation (LREC-COLING 2024)","article-title":"KET-QA: A dataset for knowledge enhanced table question answering","author":"Hu","year":"2024"},{"key":"10.1016\/j.neunet.2026.109081_bib0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2021.107565","article-title":"Local-to-global GCN with knowledge-aware representation for distantly supervised relation extraction","volume":"234","author":"Huang","year":"2021","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.neunet.2026.109081_bib0021","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.111545","article-title":"Document-level relation extraction with global and path dependencies","volume":"289","author":"Jia","year":"2024","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.neunet.2026.109081_bib0022","series-title":"Proceedings of the international joint conference on neural networks (IJCNN)","article-title":"Distantly supervised relation extraction based on non-taxonomic relation and self-optimization","author":"Jian","year":"2024"},{"key":"10.1016\/j.neunet.2026.109081_bib0023","series-title":"Understanding distantly supervised relation extraction through semantic error analysis","author":"Kalo","year":"2022"},{"key":"10.1016\/j.neunet.2026.109081_bib0024","series-title":"Findings of the association for computational linguistics: ACL","article-title":"HiCLRE: A hierarchical contrastive learning framework for distantly supervised relation extraction","author":"Li","year":"2022"},{"key":"10.1016\/j.neunet.2026.109081_bib0025","series-title":"Proceedings of the 7th international conference on machine learning and soft computing","article-title":"LDRC: Long-tail distantly supervised relation extraction via contrastive learning","author":"Li","year":"2023"},{"key":"10.1016\/j.neunet.2026.109081_bib0026","doi-asserted-by":"crossref","first-page":"2156","DOI":"10.1109\/TCBB.2024.3451348","article-title":"Relation extraction in biomedical texts: A cross-sentence approach","volume":"21","author":"Li","year":"2024","journal-title":"IEEE\/ACM Transactions on Computational Biology and Bioinformatics"},{"issue":"7","key":"10.1016\/j.neunet.2026.109081_bib0027","doi-asserted-by":"crossref","first-page":"6852","DOI":"10.1109\/TKDE.2022.3177226","article-title":"Distantly-supervised long-tailed relation extraction using constraint graphs","volume":"35","author":"Liang","year":"2022","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.neunet.2026.109081_bib0028","doi-asserted-by":"crossref","DOI":"10.1016\/j.jbi.2023.104415","article-title":"Multimodal learning on graphs for disease relation extraction","volume":"143","author":"Lin","year":"2023","journal-title":"Journal of Biomedical Informatics"},{"key":"10.1016\/j.neunet.2026.109081_bib0029","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/j.neucom.2020.04.056","article-title":"Multi-level semantic representation enhancement network for relationship extraction","volume":"403","author":"Liu","year":"2020","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neunet.2026.109081_bib0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.109800","article-title":"Knowledge graph attention mechanism for distant supervision neural relation extraction","volume":"256","author":"Liu","year":"2022","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.neunet.2026.109081_bib0031","series-title":"Proceedings of the AAAI conference on artificial intelligence","article-title":"Universal information extraction as unified semantic matching","volume":"37","author":"Lou","year":"2023"},{"issue":"5","key":"10.1016\/j.neunet.2026.109081_bib0032","doi-asserted-by":"crossref","first-page":"Bbac282","DOI":"10.1093\/bib\/bbac282","article-title":"BioRED: A rich biomedical relation extraction dataset","volume":"23","author":"Luo","year":"2022","journal-title":"Briefings in Bioinformatics"},{"key":"10.1016\/j.neunet.2026.109081_bib0033","series-title":"Proceedings of the ICASSP 2025-2025 IEEE international conference on acoustics, speech and signal processing (ICASSP)","article-title":"Gega: Graph convolutional networks and evidence retrieval guided attention for enhanced document-level relation extraction","author":"Mao","year":"2025"},{"key":"10.1016\/j.neunet.2026.109081_bib0034","doi-asserted-by":"crossref","unstructured":"Martinelli, M., et al. \"A domain-specific curated benchmark for entity and document-level relation extraction.\" arXiv preprint arXiv:2602.04320 (2026), 10.48550\/arXiv.2602.04320.","DOI":"10.18653\/v1\/2026.findings-eacl.301"},{"key":"10.1016\/j.neunet.2026.109081_bib0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2026.115359","article-title":"DOREMI: Optimizing long tail predictions in document-level relation extraction","volume":"337","author":"Menotti","year":"2026","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.neunet.2026.109081_bib0036","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106757","article-title":"Multi-relational graph contrastive learning with learnable graph augmentation","volume":"181","author":"Mo","year":"2025","journal-title":"Neural Networks"},{"key":"10.1016\/j.neunet.2026.109081_bib0037","series-title":"Findings of the association for computational linguistics: ACL-IJCNLP","article-title":"KGPool: Dynamic knowledge graph context selection for relation extraction","author":"Nadgeri","year":"2021"},{"issue":"5","key":"10.1016\/j.neunet.2026.109081_bib0038","doi-asserted-by":"crossref","first-page":"2953","DOI":"10.1109\/TFUZZ.2024.3364694","article-title":"A fuzzy graph convolutional network model for sentence-level sentiment analysis","volume":"32","author":"Phan","year":"2024","journal-title":"IEEE Transactions on Fuzzy Systems"},{"key":"10.1016\/j.neunet.2026.109081_bib0039","series-title":"Proceedings of the 62nd annual meeting of the association for computational linguistics","article-title":"End-to-end learning of logical rules for enhancing document-level relation extraction","volume":"1","author":"Qi","year":"2024"},{"key":"10.1016\/j.neunet.2026.109081_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.129684","article-title":"Type affinity network for distantly supervised relation extraction","volume":"630","author":"Song","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neunet.2026.109081_bib0041","series-title":"Proceedings of the 28th international conference on computational linguistics","article-title":"CoLAKE: Contextualized language and knowledge embedding","author":"Sun","year":"2020"},{"key":"10.1016\/j.neunet.2026.109081_bib0042","series-title":"Proceedings of the conference on empirical methods in natural language processing","article-title":"RESIDE: Improving distantly-supervised neural relation extraction using side information","author":"Vashishth","year":"2018"},{"key":"10.1016\/j.neunet.2026.109081_bib0043","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1162\/tacl_a_00021","article-title":"Constructing datasets for multi-hop reading comprehension across documents","volume":"6","author":"Welbl","year":"2018","journal-title":"Transactions of the Association for Computational Linguistics"},{"key":"10.1016\/j.neunet.2026.109081_bib0044","doi-asserted-by":"crossref","first-page":"1153","DOI":"10.1007\/s10844-025-00932-w","article-title":"Distant supervised relation extraction with label entailment and collaborative denoising","volume":"63","author":"Xie","year":"2025","journal-title":"Journal of Intelligent Information Systems"},{"key":"10.1016\/j.neunet.2026.109081_bib0045","series-title":"Proceedings of the conference of the North American chapter of the association for computational linguistics: Human language technologies","article-title":"Connecting language and knowledge with heterogeneous representations for neural relation extraction","volume":"1","author":"Xu","year":"2019"},{"key":"10.1016\/j.neunet.2026.109081_bib0046","doi-asserted-by":"crossref","first-page":"516","DOI":"10.1016\/j.neucom.2021.12.044","article-title":"BERT gated multi-window attention network for relation extraction","volume":"492","author":"Xu","year":"2022","journal-title":"Neurocomputing"},{"issue":"7","key":"10.1016\/j.neunet.2026.109081_bib0047","doi-asserted-by":"crossref","first-page":"3091","DOI":"10.1109\/TKDE.2024.3360454","article-title":"Give us the facts: Enhancing large language models with knowledge graphs for fact-aware language modeling","volume":"36","author":"Yang","year":"2024","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.neunet.2026.109081_bib0048","series-title":"Proceedings of the 57th annual meeting of the association for computational linguistics","article-title":"DocRED: A large-scale document-level relation extraction dataset","author":"Yao","year":"2019"},{"key":"10.1016\/j.neunet.2026.109081_bib0049","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.aiopen.2021.02.002","article-title":"A comprehensive survey of entity alignment for knowledge graphs","volume":"2","author":"Zeng","year":"2021","journal-title":"AI Open"},{"key":"10.1016\/j.neunet.2026.109081_bib0050","series-title":"Proceedings of the thirtieth international joint conference on artificial intelligence. International joint conferences on artificial intelligence organization","article-title":"Document-level relation extraction as semantic segmentation","author":"Zhang","year":"2021"},{"key":"10.1016\/j.neunet.2026.109081_bib0051","series-title":"Proceedings of the 44th international ACM SIGIR conference on research and development in information retrieval","article-title":"Readsre: Retrieval-augmented distantly supervised relation extraction","author":"Zhang","year":"2021"},{"issue":"11","key":"10.1016\/j.neunet.2026.109081_bib0052","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3674501","article-title":"A comprehensive survey on relation extraction: Recent advances and new frontiers","volume":"56","author":"Zhao","year":"2024","journal-title":"ACM Computing Surveys"},{"key":"10.1016\/j.neunet.2026.109081_bib0053","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.110479","article-title":"Thoughtful and cautious reasoning: A fine-tuned knowledge graph-based multi-hop question answering framework","volume":"150","author":"Zheng","year":"2025","journal-title":"Engineering Applications of Artificial Intelligence"},{"issue":"3","key":"10.1016\/j.neunet.2026.109081_bib0054","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1007\/s11063-024-11497-0","article-title":"Distantly supervised relation extraction based on residual attention and self learning","volume":"56","author":"Zheng","year":"2024","journal-title":"Neural Processing Letters"},{"key":"10.1016\/j.neunet.2026.109081_bib0055","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.112328","article-title":"Deconstructing reasoning paths and attending to semantic guidance for document-level relation extraction","volume":"301","author":"Zhong","year":"2024","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.neunet.2026.109081_bib0056","series-title":"Proceedings of the AAAI conference on artificial intelligence","article-title":"Improving distantly supervised relation extraction by natural language inference","volume":"37","author":"Zhou","year":"2023"}],"container-title":["Neural Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026005411?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026005411?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,23]],"date-time":"2026-05-23T21:57:42Z","timestamp":1779573462000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0893608026005411"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":56,"alternative-id":["S0893608026005411"],"URL":"https:\/\/doi.org\/10.1016\/j.neunet.2026.109081","relation":{},"ISSN":["0893-6080"],"issn-type":[{"value":"0893-6080","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"KAB: A knowledge-aligned benchmark for reproducible evaluation of distantly supervised relation extraction","name":"articletitle","label":"Article Title"},{"value":"Neural Networks","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neunet.2026.109081","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"109081"}}